Deep learning in environmental remote sensing: Achievements and challenges

Q Yuan, H Shen, T Li, Z Li, S Li, Y Jiang, H Xu… - Remote sensing of …, 2020 - Elsevier
Various forms of machine learning (ML) methods have historically played a valuable role in
environmental remote sensing research. With an increasing amount of “big data” from earth …

[HTML][HTML] Remote sensing of soil degradation: Progress and perspective

J Wang, J Zhen, W Hu, S Chen, I Lizaga… - International Soil and …, 2023 - Elsevier
Soils constitute one of the most critical natural resources and maintaining their health is vital
for agricultural development and ecological sustainability, providing many essential …

Potential for artificial intelligence (AI) and machine learning (ML) applications in biodiversity conservation, managing forests, and related services in India

KN Shivaprakash, N Swami, S Mysorekar, R Arora… - Sustainability, 2022 - mdpi.com
The recent advancement in data science coupled with the revolution in digital and satellite
technology has improved the potential for artificial intelligence (AI) applications in the …

Optical remote sensing and the retrieval of terrestrial vegetation bio-geophysical properties–A review

J Verrelst, G Camps-Valls, J Muñoz-Marí… - ISPRS Journal of …, 2015 - Elsevier
Forthcoming superspectral satellite missions dedicated to land monitoring, as well as
planned imaging spectrometers, will unleash an unprecedented data stream. The …

Hybrid retrieval of crop traits from multi-temporal PRISMA hyperspectral imagery

G Tagliabue, M Boschetti, G Bramati, G Candiani… - ISPRS Journal of …, 2022 - Elsevier
The recently launched and upcoming hyperspectral satellite missions, featuring contiguous
visible-to-shortwave infrared spectral information, are opening unprecedented opportunities …

Advances in hyperspectral remote sensing of vegetation and agricultural crops

PS Thenkabail, JG Lyon, A Huete - … , Sensor Systems, Spectral …, 2018 - taylorfrancis.com
Hyperspectral data (Table 1) is acquired as continuous narrowbands (eg, each band with 1
to 10 nanometer or nm bandwidths) over a range of electromagnetic spectrum (eg, 400 …

[LIBRO][B] Fundamentals of satellite remote sensing: An environmental approach

E Chuvieco - 2020 - taylorfrancis.com
Fundamentals of Satellite Remote Sensing: An Environmental Approach, Third Edition, is a
definitive guide to remote sensing systems that focuses on satellite-based remote sensing …

PROSPECT+ SAIL models: A review of use for vegetation characterization

S Jacquemoud, W Verhoef, F Baret, C Bacour… - Remote sensing of …, 2009 - Elsevier
The combined PROSPECT leaf optical properties model and SAIL canopy bidirectional
reflectance model, also referred to as PROSAIL, has been used for about sixteen years to …

Remote sensing of plant functional types

SL Ustin, JA Gamon - New Phytologist, 2010 - Wiley Online Library
Conceptually, plant functional types represent a classification scheme between species and
broad vegetation types. Historically, these were based on physiological, structural and/or …

A global review of remote sensing of live fuel moisture content for fire danger assessment: Moving towards operational products

M Yebra, PE Dennison, E Chuvieco, D Riaño… - Remote Sensing of …, 2013 - Elsevier
One of the primary variables affecting ignition and spread of wildfire is fuel moisture content
(FMC). Live FMC (LFMC) is responsive to long term climate and plant adaptations to …